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  • Open Access

    ARTICLE

    A Robust Single-Sensor MPPT Strategy for Shaded Photovoltaic-Battery System

    A. N. M. Alahmadi1, Hegazy Rezk2,3,*

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 63-71, 2021, DOI:10.32604/csse.2021.015029 - 05 February 2021

    Abstract A robust single-sensor global maximum power point tracking (MPPT) strategy based on modern optimization for photovoltaic systems considering shading conditions is proposed in this work. The proposed strategy is designed for battery charging applications and direct current (DC) microgrids. Under normal operation, the curve of photovoltaic (PV) output power versus PV voltage contains only a single peak point. This point can be simply captured using any traditional tracking method like perturb and observe. However, this situation is completely different during the shadowing effect where several peaks appear on the power voltage curve. Most of these… More >

  • Open Access

    ARTICLE

    RP-NBSR: A Novel Network Attack Detection Model Based on Machine Learning

    Zihao Shen1,2, Hui Wang1,*, Kun Liu1, Peiqian Liu1, Menglong Ba1, MengYao Zhao3

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 121-133, 2021, DOI:10.32604/csse.2021.014988 - 05 February 2021

    Abstract The rapid progress of the Internet has exposed networks to an increased number of threats. Intrusion detection technology can effectively protect network security against malicious attacks. In this paper, we propose a ReliefF-P-Naive Bayes and softmax regression (RP-NBSR) model based on machine learning for network attack detection to improve the false detection rate and F1 score of unknown intrusion behavior. In the proposed model, the Pearson correlation coefficient is introduced to compensate for deficiencies in correlation analysis between features by the ReliefF feature selection algorithm, and a ReliefF-Pearson correlation coefficient (ReliefF-P) algorithm is proposed. Then, More >

  • Open Access

    ARTICLE

    Anomaly Detection in ICS Datasets with Machine Learning Algorithms

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Farah Diyana Abdul Rahman, Mohammad Tahir2

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 33-46, 2021, DOI:10.32604/csse.2021.014384 - 05 February 2021

    Abstract An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of More >

  • Open Access

    ARTICLE

    A Generative Adversarial Networks for Log Anomaly Detection

    Xiaoyu Duan1, Shi Ying1,*, Wanli Yuan1, Hailong Cheng1, Xiang Yin2

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 135-148, 2021, DOI:10.32604/csse.2021.014030 - 05 February 2021

    Abstract Detecting anomaly logs is a great significance step for guarding system faults. Due to the uncertainty of abnormal log types, lack of real anomaly logs and accurately labeled log datasets. Existing technologies cannot be enough for detecting complex and various log point anomalies by using human-defined rules. We propose a log anomaly detection method based on Generative Adversarial Networks (GAN). This method uses the Encoder-Decoder framework based on Long Short-Term Memory (LSTM) network as the generator, takes the log keywords as the input of the encoder, and the decoder outputs the generated log template. The More >

  • Open Access

    ARTICLE

    COVID-19 Pandemic Data Predict the Stock Market

    Abdulaziz Almehmadi*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 451-460, 2021, DOI:10.32604/csse.2021.015309 - 18 January 2021

    Abstract Unlike the 2007–2008 market crash, which was caused by a banking failure and led to an economic recession, the 1918 influenza pandemic triggered a worldwide financial depression. Pandemics usually affect the global economy, and the COVID-19 pandemic is no exception. Many stock markets have fallen over 40%, and companies are shutting down, ending contracts, and issuing voluntary and involuntary leaves for thousands of employees. These economic effects have led to an increase in unemployment rates, crime, and instability. Studying pandemics’ economic effects, especially on the stock market, has not been urgent or feasible until recently.… More >

  • Open Access

    REVIEW

    A Review of Dynamic Resource Management in Cloud Computing Environments

    Mohammad Aldossary*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 461-476, 2021, DOI:10.32604/csse.2021.014975 - 18 January 2021

    Abstract In a cloud environment, Virtual Machines (VMs) consolidation and resource provisioning are used to address the issues of workload fluctuations. VM consolidation aims to move the VMs from one host to another in order to reduce the number of active hosts and save power. Whereas resource provisioning attempts to provide additional resource capacity to the VMs as needed in order to meet Quality of Service (QoS) requirements. However, these techniques have a set of limitations in terms of the additional costs related to migration and scaling time, and energy overhead that need further consideration. Therefore, More >

  • Open Access

    ARTICLE

    Efficient Training of Multi-Layer Neural Networks to Achieve Faster Validation

    Adel Saad Assiri*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 435-450, 2021, DOI:10.32604/csse.2021.014894 - 18 January 2021

    Abstract Artificial neural networks (ANNs) are one of the hottest topics in computer science and artificial intelligence due to their potential and advantages in analyzing real-world problems in various disciplines, including but not limited to physics, biology, chemistry, and engineering. However, ANNs lack several key characteristics of biological neural networks, such as sparsity, scale-freeness, and small-worldness. The concept of sparse and scale-free neural networks has been introduced to fill this gap. Network sparsity is implemented by removing weak weights between neurons during the learning process and replacing them with random weights. When the network is initialized, More >

  • Open Access

    ARTICLE

    On Edge Irregular Reflexive Labeling of Categorical Product of Two Paths

    Muhammad Javed Azhar Khan1, Muhammad Ibrahim1,*, Ali Ahmad2

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 485-492, 2021, DOI:10.32604/csse.2021.014810 - 18 January 2021

    Abstract Among the huge diversity of ideas that show up while studying graph theory, one that has obtained a lot of popularity is the concept of labelings of graphs. Graph labelings give valuable mathematical models for a wide scope of applications in high technologies (cryptography, astronomy, data security, various coding theory problems, communication networks, etc.). A labeling or a valuation of a graph is any mapping that sends a certain set of graph elements to a certain set of numbers subject to certain conditions. Graph labeling is a mapping of elements of the graph, i.e., vertex… More >

  • Open Access

    ARTICLE

    ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images

    Yanyun Jiang1, Yuanjie Zheng1,2,*, Xiaodan Sui1, Wanzhen Jiao3, Yunlong He4, Weikuan Jia1

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 537-549, 2021, DOI:10.32604/csse.2021.014578 - 18 January 2021

    Abstract Multispectral imaging (MSI) technique is often used to capture images of the fundus by illuminating it with different wavelengths of light. However, these images are taken at different points in time such that eyeball movements can cause misalignment between consecutive images. The multispectral image sequence reveals important information in the form of retinal and choroidal blood vessel maps, which can help ophthalmologists to analyze the morphology of these blood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deep… More >

  • Open Access

    ARTICLE

    A Storage Optimization Scheme for Blockchain Transaction Databases

    Jingyu Zhang1,2, Siqi Zhong1, Jin Wang1,3, Xiaofeng Yu4,*, Osama Alfarraj5

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 521-535, 2021, DOI:10.32604/csse.2021.014530 - 18 January 2021

    Abstract As the typical peer-to-peer distributed networks, blockchain systems require each node to copy a complete transaction database, so as to ensure new transactions can by verified independently. In a blockchain system (e.g., bitcoin system), the node does not rely on any central organization, and every node keeps an entire copy of the transaction database. However, this feature determines that the size of blockchain transaction database is growing rapidly. Therefore, with the continuous system operations, the node memory also needs to be expanded to support the system running. Especially in the big data era, the increasing More >

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